Results 41 to 50 of about 151,127 (170)
Simulated redistricting plans for the analysis and evaluation of redistricting in the United States
Scientific Data, 2022 Measurement(s) redistricting, partisanship Technology Type(s) sequential Monte Carlo algorithm Factor Type(s) population deviation • compactness • county splits • racial composition • municipality splits Sample Characteristic - Organism Congressional ...
Cory McCartan +7 more
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An Introduction to Sequential Monte Carlo
, 2020 Particle filters are about 25 years old. Initially confined to the so-called “filtering problem” (the sequential analysis of state-space models), they are now routinely applied to a large variety of sequential and non-sequential tasks and have evolved to the broader Sequential Monte Carlo (SMC) framework.
Chopin, Nicolas +1 more
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Bayesian model selection for multilevel models using integrated likelihoods.
PLoS ONE, 2023 Multilevel linear models allow flexible statistical modelling of complex data with different levels of stratification. Identifying the most appropriate model from the large set of possible candidates is a challenging problem. In the Bayesian setting, the
Tom Edinburgh, Ari Ercole, Stephen Eglen
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Sequential Monte Carlo Methods in the nimble and nimbleSMC R Packages
Journal of Statistical Software, 2021 nimble is an R package for constructing algorithms and conducting inference on hierarchical models. The nimble package provides a unique combination of flexible model specification and the ability to program model-generic algorithms.
Nicholas Michaud +4 more
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, 2017 SMC (Sequential Monte Carlo) is a class of Monte Carlo algorithms for filtering and related sequential problems. Gerber and Chopin (2015) introduced SQMC (Sequential quasi-Monte Carlo), a QMC version of SMC.
A Doucet +16 more
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An Adaptive Sequential Monte Carlo Sampler [PDF]
Bayesian Analysis, 2013 41 pages, 1 ...
Fearnhead, Paul, Taylor, Benjamin M.
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Reliability Evaluation of a Metro Traction Substation Based on the Monte Carlo Method
IEEE Access, 2019 The study of a metro traction power supply system reliability makes a significant contribution to researching on new power supply principles and configuration, and also providing a reference for system design and operation.
Kunpeng Li +4 more
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Accelerated Iterated Filtering
Austrian Journal of Statistics, 2023 Simulation-based inferences have attracted much attention in recent years, as the direct computation of the likelihood function in many real-world problems is difficult or even impossible.
Dao Nguyen
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Sequential Monte Carlo with model tempering
Studies in Nonlinear Dynamics & Econometrics, 2023 Abstract Modern macroeconometrics often relies on time series models for which it is time-consuming to evaluate the likelihood function. We demonstrate how Bayesian computations for such models can be drastically accelerated by reweighting and mutating posterior draws from an approximating model that allows for fast likelihood ...
Marko Mlikota, Frank Schorfheide
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Statistical Inference for Partially Observed Markov Processes via the R Package pomp
Journal of Statistical Software, 2016 Partially observed Markov process (POMP) models, also known as hidden Markov models or state space models, are ubiquitous tools for time series analysis.
Aaron A. King +2 more
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